The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
데이터 전송 전 프레임 동기화 감지는 수중 음향 통신(UAC) 네트워크의 수명과 공존에 직접적인 영향을 미치는 중요한 모듈입니다. 선형 주파수 변조(LFM)는 동기화에 일반적으로 사용되는 프레임 프리앰블 신호입니다. UAC에서는 지상 무선 통신과 달리 강한 버스트 노이즈가 자주 나타납니다. 전송 거리가 길고 신호 대 잡음비가 낮기 때문에 강한 단거리 버스티 잡음은 기존 분수 푸리에 변환(FrFT) 감지의 정확도를 크게 떨어뜨립니다. 우리는 이 문제를 해결하기 위해 다중 세그먼트 검증 분수 푸리에 변환(MFrFT) 프리앰블 감지 알고리즘을 제안합니다. 제안하는 알고리즘에서는 인접 FrFT 연산을 4번 수행한다. 그리고 LFM 신호는 '이중선 상관 메커니즘'이라고 불리는 인접한 XNUMX개의 피크 지점 중 쌍으로 연결된 두 선 사이의 선형 상관 관계를 관찰하여 식별합니다. LFM 신호의 정확한 시작 시간은 인접한 FrFT의 피크 주파수에 따라 찾을 수 있습니다. 더 중요한 것은 MFrFT가 계산 복잡성을 증가시키지 않는다는 것입니다. 실험 결과는 제안된 알고리즘이 기존 FrFT 검출 방법과 비교하여 훨씬 낮은 오류 검출률로 신호 시작점과 버스티 잡음을 효과적으로 구별할 수 있어 재전송 비용을 최소화할 수 있음을 보여줍니다.
Guojin LIAO
Liaoning University of Technology
Yongpeng ZUO
Cadence Design System Inc.
Qiao LIAO
Tianjin University
Xiaofeng TIAN
Liaoning University of Technology
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부
Guojin LIAO, Yongpeng ZUO, Qiao LIAO, Xiaofeng TIAN, "Multi-Segment Verification FrFT Frame Synchronization Detection in Underwater Acoustic Communications" in IEICE TRANSACTIONS on Communications,
vol. E106-B, no. 12, pp. 1501-1509, December 2023, doi: 10.1587/transcom.2023EBP3048.
Abstract: Frame synchronization detection before data transmission is an important module which directly affects the lifetime and coexistence of underwater acoustic communication (UAC) networks, where linear frequency modulation (LFM) is a frame preamble signal commonly used for synchronization. Unlike terrestrial wireless communications, strong bursty noise frequently appears in UAC. Due to the long transmission distance and the low signal-to-noise ratio, strong short-distance bursty noise will greatly reduce the accuracy of conventional fractional fourier transform (FrFT) detection. We propose a multi-segment verification fractional fourier transform (MFrFT) preamble detection algorithm to address this challenge. In the proposed algorithm, 4 times of adjacent FrFT operations are carried out. And the LFM signal identifies by observing the linear correlation between two lines connected in pair among three adjacent peak points, called ‘dual-line-correlation mechanism’. The accurate starting time of the LFM signal can be found according to the peak frequency of the adjacent FrFT. More importantly, MFrFT do not result in an increase in computational complexity. Compared with the conventional FrFT detection method, experimental results show that the proposed algorithm can effectively distinguish between signal starting points and bursty noise with much lower error detection rate, which in turn minimizes the cost of retransmission.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2023EBP3048/_p
부
@ARTICLE{e106-b_12_1501,
author={Guojin LIAO, Yongpeng ZUO, Qiao LIAO, Xiaofeng TIAN, },
journal={IEICE TRANSACTIONS on Communications},
title={Multi-Segment Verification FrFT Frame Synchronization Detection in Underwater Acoustic Communications},
year={2023},
volume={E106-B},
number={12},
pages={1501-1509},
abstract={Frame synchronization detection before data transmission is an important module which directly affects the lifetime and coexistence of underwater acoustic communication (UAC) networks, where linear frequency modulation (LFM) is a frame preamble signal commonly used for synchronization. Unlike terrestrial wireless communications, strong bursty noise frequently appears in UAC. Due to the long transmission distance and the low signal-to-noise ratio, strong short-distance bursty noise will greatly reduce the accuracy of conventional fractional fourier transform (FrFT) detection. We propose a multi-segment verification fractional fourier transform (MFrFT) preamble detection algorithm to address this challenge. In the proposed algorithm, 4 times of adjacent FrFT operations are carried out. And the LFM signal identifies by observing the linear correlation between two lines connected in pair among three adjacent peak points, called ‘dual-line-correlation mechanism’. The accurate starting time of the LFM signal can be found according to the peak frequency of the adjacent FrFT. More importantly, MFrFT do not result in an increase in computational complexity. Compared with the conventional FrFT detection method, experimental results show that the proposed algorithm can effectively distinguish between signal starting points and bursty noise with much lower error detection rate, which in turn minimizes the cost of retransmission.},
keywords={},
doi={10.1587/transcom.2023EBP3048},
ISSN={1745-1345},
month={December},}
부
TY - JOUR
TI - Multi-Segment Verification FrFT Frame Synchronization Detection in Underwater Acoustic Communications
T2 - IEICE TRANSACTIONS on Communications
SP - 1501
EP - 1509
AU - Guojin LIAO
AU - Yongpeng ZUO
AU - Qiao LIAO
AU - Xiaofeng TIAN
PY - 2023
DO - 10.1587/transcom.2023EBP3048
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E106-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2023
AB - Frame synchronization detection before data transmission is an important module which directly affects the lifetime and coexistence of underwater acoustic communication (UAC) networks, where linear frequency modulation (LFM) is a frame preamble signal commonly used for synchronization. Unlike terrestrial wireless communications, strong bursty noise frequently appears in UAC. Due to the long transmission distance and the low signal-to-noise ratio, strong short-distance bursty noise will greatly reduce the accuracy of conventional fractional fourier transform (FrFT) detection. We propose a multi-segment verification fractional fourier transform (MFrFT) preamble detection algorithm to address this challenge. In the proposed algorithm, 4 times of adjacent FrFT operations are carried out. And the LFM signal identifies by observing the linear correlation between two lines connected in pair among three adjacent peak points, called ‘dual-line-correlation mechanism’. The accurate starting time of the LFM signal can be found according to the peak frequency of the adjacent FrFT. More importantly, MFrFT do not result in an increase in computational complexity. Compared with the conventional FrFT detection method, experimental results show that the proposed algorithm can effectively distinguish between signal starting points and bursty noise with much lower error detection rate, which in turn minimizes the cost of retransmission.
ER -